Comparative Study on Multiobjective Power Unit Coordinated Control Problem via Differential Evolution and Particle Swarm Optimization Algorithms

Abstract:

Power unit coordinated control (PUCC) problem was being focused by many optimizers as a serious task to be tackled in several aspects. Through this paper differential evolution (DE) and particle swarm optimization (PSO) algorithms are implemented to solve the PUCC problem. With considering four objectives to be optimized: minimization of tracking error in load power demand, fuel consumption, throttling losses due to steam control valve, and feeding water. Simulation experiments are made through case-study by aid of MATLAB programs to develop the required comparison through the two algorithms.

• Periodical: Advanced Materials Research (Volume 650)
• Pages: 470-475
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.650.470
• Online since: January 2013
• Authors: Zain Zaharn, Rui Feng Shi, Xiang Jie Liu
• Keywords: Differential Evolution, Multi-Objective Power Unit Coordinated Control Problem, Particle Swarm Optimization (PSO)

References

[1] Leĭzerovich, A.S., Steam turbines for modern fossil-fuel power plants. The Fairmont Press, Inc. (2008).

[2] Lee, K.Y., Modern heuristic optimization techniques: Theory and applications to power systems. Vol. 39, Wiley-IEEE press. (2008).

[3] Garduno-Ramirez, R. and K.Y. Lee, Multiobjective optimal power plant operation through.

[4] coordinate control with pressure set point scheduling. Energy Conversion, IEEE Transactions on, Vol. 16, No. 2 (2001), pp.115-122.

DOI: 10.1109/60.921461

[5] Heo, J.S., K.Y. Lee, and R. Garduno-Ramirez, Multiobjective control of power plants using.

[6] particle swarm optimization techniques. Energy Conversion, IEEE Transactions on, Vol. 21, No. 2: (2006), pp.552-561.

[7] Van Sickel, J.H., P. Venkatesh, and K.Y. Lee. Analysis of the pareto front of a multi-objective optimization problem for a fossil fuel power plant. IEEE, (2008).

DOI: 10.1109/pes.2008.4596904

[8] Head, J.D., et al. Implementation of a multi-agent system for optimized multiobjective powerplant control. IEEE (2010).

[9] Liu, X., P. Guan, and C. Chan, Nonlinear Multivariable Power Plant Coordinate Control by.

[10] Constrained Predictive Scheme. Control Systems Technology, IEEE Transactions on, Vol. 18, No. 5 (2010), pp.1116-1125.

[11] Li, S., et al., A new coordinated control strategy for boiler-turbine system of coal-fired power plant. Control Systems Technology, IEEE Transactions on, Vol. 13, No. 6 (2005), pp.943-954.

DOI: 10.1109/tcst.2005.854319

[12] Chakraborty, U.K., Advances in differential evolution. Vol. 143. Springer-Verlag New York Incorporated. (2008).

[13] Tasgetiren, M.F. and P. Suganthan. A multi-populated differential evolution algorithm forsolving constrained optimization problem. IEEE. (2006).

DOI: 10.1109/cec.2006.1688287

[14] Clerc, M., Particle swarm optimization. Wiley-ISTE. (2006).

[15] Bell, R. and K.J. Åström, Dynamic models for boiler-turbine-alternator units: data logs and.

[16] parameter estimation for a 160 MW unit. Lund Institute of Technology, Dept. of Automatic Control. (1987).